Triple

T21453563
Position Surface form Disambiguated ID Type / Status
Subject SR 25 (Alabama) E529278 entity
Predicate locatedIn P40 FINISHED
Object Odenville, Alabama NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Odenville, Alabama | Statement: [SR 25 (Alabama), locatedIn, Odenville, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odenville, Alabama
Context triple: [SR 25 (Alabama), locatedIn, Odenville, Alabama]
  • A. Odenville, Alabama chosen
    Odenville, Alabama is a small town in central Alabama known for its rural character and location within the Birmingham metropolitan area.
  • B. Ensley, Alabama
    Ensley, Alabama is a historic industrial neighborhood in Birmingham that developed as a major steelmaking and manufacturing center in the late 19th and early 20th centuries.
  • C. Riverside, Alabama
    Riverside, Alabama is a small community in St. Clair County known for its location along the Coosa River in central Alabama.
  • D. Townley, Alabama
    Townley, Alabama is a small unincorporated community located in Walker County in the north-central part of the state.
  • E. Courtland, Alabama
    Courtland, Alabama is a small historic town in northern Alabama known for its 19th-century architecture and role in the region’s early transportation and cotton economy.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69e0c457579481909db68053ed99750c completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9d50b88819081a771596d0a2b2b completed April 23, 2026, 9:43 a.m.
Created at: April 16, 2026, 6:07 p.m.